Evidence map›Paper›PMID 34572557›Full record

ArticleBiomolecules2021

Computational Analysis of Naturally Occurring Aristolochic Acid Analogues and Their Biological Sources.

Tingjun Xu, Weiming Chen, Junhong Zhou, Jingfang Dai, Yingyong Li, Yingli Zhao

Abstract read
In one paragraph

Article in Biomolecules, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Immunomodulatory Potential of the IndustrializedFoods (Basel, Switzerland) · 2021
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Tingjun XuShanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 LingLing Road, Shanghai 200032, China.ORCID 0000-0002-5529-1875
Weiming ChenShanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 LingLing Road, Shanghai 200032, China.
Junhong ZhouShanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 LingLing Road, Shanghai 200032, China.
Jingfang DaiShanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 LingLing Road, Shanghai 200032, China.
Yingyong LiShanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 LingLing Road, Shanghai 200032, China.
Yingli ZhaoShanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 LingLing Road, Shanghai 200032, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aristolochic acids are known for nephrotoxicity, and implicated in multiple cancer types such as hepatocellular carcinomas demonstrated by recent studies. Natural products that are analogues to aristolochic acids have been constantly isolated from organisms; a larger chemical space of these compounds and a wider coverage of biological sources should be determined in consideration of the potential hazard of aristolochic acid analogues and the wide distribution of their biological sources in the nature. Therefore, we carried out an in silico research of naturally occurring aristolochic acid analogues and their biological sources, as a supplement to existing studies. The result shows a chemical space of 238 naturally occurring aristolochic acid analogues that are present in 175 species of biological sources including 44 traditional medicines. With the computational estimation for toxicity and the implication in hazard assessment of a biological source with the presence of aristolochic acid analogues, we propose that additional awareness should be raised to the public for avoidance of toxic species, especially those that are used as herbal medicines and easily accessible.

Indexed as

Aristolochic AcidsComputational BiologyDrug Evaluation, PreclinicalPhylogenyStatic ElectricityToxicity Tests, AcuteAristolochic Acidsaristolochic acid analoguesbiological sourcescarcinogenic substancecomputational analysiscomputer predicted toxicitynatural productstoxic herbalstraditional medicinesvirtual screening

Identifiers

PMID34572557
PMCPMC8471445

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.